Xavier Amatriain

Information Systems · with Oliver · 2008–2020

A researcher in the Science corpus: 7 papers; trusts 15 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 40 citations into it; #2,486 of 8,771 by trust here, #1,413 by citations
• Artificial Intelligence — 33 citations into it
• Computer Vision and Pattern Recognition — 25 citations into it
• Management Science and Operations Research — 13 citations into it; #3,718 of 11,946 by trust here, #1,836 by citations
• Computer Networks and Communications — 9 citations into it
• Statistical Learning Theory — 6 citations into it
• Marketing — 6 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Xavier Amatriain trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. William W. Cohen
2. Badrul Munir Sarwar
3. Ian T. Jolliffe
4. Ronan Collobert
5. Gene H. Golub
6. Koji Miyahara
7. George Karypis
8. J. Breese
9. J. Konstan
10. Robert M. Bell

Who trusts Xavier Amatriain overall

1. Steffen Rendle
2. Charu C. Aggarwal
3. Senzhang Wang
4. Jie Lu
5. Yu Zheng
6. Evangelos E. Papalexakis
7. Paul Covington
8. Yilun Wang
9. Yue Shi
10. Xia Ning

Papers from Xavier Amatriain's perspective

Ordered by how strongly the researchers Xavier Amatriain trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering (2010) — 860 citations
• Temporal diversity in recommender systems (2010) — 328 citations
• Watching television over an IP network (2008) — 300 citations
• Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs (2020) — 85 citations
• Data Mining Methods for Recommender Systems (2015) — 284 citations
• Building industrial-scale real-world recommender systems (2012) — 33 citations
• Music recommendations with temporal context awareness (2010) — 37 citations